Traditional systems to detect and/or track a user feature may utilize image-processing techniques that maximize detail for the user feature. For example, a red-blue-green (RGB) color spectrum or relatively high resolution may be used to detect and/or track the user feature. In addition, a depth camera may be used to measure a set of points on the user feature and output the set of points in a data file as a point cloud to detect and/or track the user feature in three-dimensional (3D) space. In this regard, stereo matching performed prior to generating the point cloud may require processing of entire stereo images. Moreover, z-distance for the user feature in a 3D coordinate system and/or touching by the user feature may be determined using capacitive sensing devices (e.g., touch screen, etc.) or mechanical sensing devices (e.g., keyboard, etc.). The traditional systems, therefore, may require extra hardware such as a touch-sensitive panel, waste computing resources, delay detection, delay tracking, require various peripheral devices, lack pressure detection, and so on. Thus, there is considerable room for improvement to detect a user feature, track a user feature, detect a touch event, detect a finger press event, and/or control a device using a user feature.